def shadow_mask_array(image_difference_array, threshold=-5500, filter_size=13, morphing_size=0): # TODO: Is it 0 in morphing_size?? is not 10??
'''
This method returns a mask for the given array, it stacks all the bands into
one and filters values that match the threshold. The new array will be filled
with 0 when the values are above the threshold and 1 when the values are bellow
the threshold. We assume that shadows will have darker values when compared to
the reference array.
'''
shadows = filter_median((numpy.sum(image_difference_array[3:, :, :], axis=0) < threshold).astype(numpy.int), filter_size)
if morphing_size:
shadows = morph_dilation(shadows, morphing_size)
return shadows
def cloud_mask_array(image_difference_array, threshold=30000, filter_size=13, morphing_size=0): # TODO: Is it 0 in morphing_size?? is not 10??
'''
This method returns a mask for the given array, it stacks all the bands into
one and filters values that match the threshold. The new array will be filled
with 0 when the values are below the threshold and 1 when the values are above
the threshold. We assume that clouds will have brighter values when compared
to the reference array.
'''
clouds = filter_median((numpy.sum(image_difference_array, axis=0) > threshold).astype(numpy.int), filter_size)
if morphing_size:
clouds = morph_dilation(clouds, morphing_size)
return clouds
def shadow_mask_array(
image_difference_array,
threshold=-5500,
filter_size=13,
morphing_size=0): # TODO: Is it 0 in morphing_size?? is not 10??
'''
This method returns a mask for the given array, it stacks all the bands into
one and filters values that match the threshold. The new array will be filled
with 0 when the values are above the threshold and 1 when the values are bellow
the threshold. We assume that shadows will have darker values when compared to
the reference array.
'''
shadows = filter_median((numpy.sum(image_difference_array[3:, :, :],
axis=0) < threshold).astype(numpy.int),
filter_size)
if morphing_size:
shadows = morph_dilation(shadows, morphing_size)
return shadows
def cloud_mask_array(
image_difference_array,
threshold=30000,
filter_size=13,
morphing_size=0): # TODO: Is it 0 in morphing_size?? is not 10??
'''
This method returns a mask for the given array, it stacks all the bands into
one and filters values that match the threshold. The new array will be filled
with 0 when the values are below the threshold and 1 when the values are above
the threshold. We assume that clouds will have brighter values when compared
to the reference array.
'''
clouds = filter_median(
(numpy.sum(image_difference_array, axis=0) > threshold).astype(
numpy.int), filter_size)
if morphing_size:
clouds = morph_dilation(clouds, morphing_size)
return clouds
